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» Improving data mining utility with projective sampling
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JSS
2007
88views more  JSS 2007»
14 years 9 months ago
SQUIRE: Sequential pattern mining with quantities
Discovering sequential patterns is an important problem for many applications. Existing algorithms find qualitative sequential patterns in the sense that only items are included ...
Chulyun Kim, Jong-Hwa Lim, Raymond T. Ng, Kyuseok ...
ICDM
2006
IEEE
147views Data Mining» more  ICDM 2006»
15 years 3 months ago
Adaptive Parallel Graph Mining for CMP Architectures
Mining graph data is an increasingly popular challenge, which has practical applications in many areas, including molecular substructure discovery, web link analysis, fraud detect...
Gregory Buehrer, Srinivasan Parthasarathy, Yen-Kua...
77
Voted
NIPS
2001
14 years 11 months ago
Quantizing Density Estimators
We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
Peter Meinicke, Helge Ritter
SISAP
2008
IEEE
188views Data Mining» more  SISAP 2008»
15 years 4 months ago
High-Dimensional Similarity Retrieval Using Dimensional Choice
There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information...
Dave Tahmoush, Hanan Samet
82
Voted
ACMSE
2009
ACM
15 years 4 months ago
A hybrid approach to mining frequent sequential patterns
The mining of frequent sequential patterns has been a hot and well studied area—under the broad umbrella of research known as KDD (Knowledge Discovery and Data Mining)— for we...
Erich Allen Peterson, Peiyi Tang